Trends and Hotspots in Global Radiomics Research: A Bibliometric Analysis.

IF 2.7 4区 医学 Q3 ONCOLOGY Technology in Cancer Research & Treatment Pub Date : 2024-01-01 DOI:10.1177/15330338241235769
Minghui Zhang, Yan Wang, Mutian Lv, Li Sang, Xuemei Wang, Zijun Yu, Ziyi Yang, Zhongqing Wang, Liang Sang
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引用次数: 0

Abstract

Objectives: The purpose of this research is to summarize the structure of radiomics-based knowledge and to explore potential trends and priorities by using bibliometric analysis. Methods: Select radiomics-related publications from 2012 to October 2022 from the Science Core Collection Web site. Use VOSviewer (version 1.6.18), CiteSpace (version 6.1.3), Tableau (version 2022), Microsoft Excel and Rstudio's free online platforms (http://bibliometric.com) for co-writing, co-citing, and co-occurrence analysis of countries, institutions, authors, references, and keywords in the field. The visual analysis is also carried out on it. Results: The study included 6428 articles. Since 2012, there has been an increase in research papers based on radiomics. Judging by publications, China has made the largest contribution in this area. We identify the most productive institutions and authors as Fudan University and Tianjie. The top three magazines with the most publications are《FRONTIERS IN ONCOLOGY》, 《EUROPEAN RADIOLOGY》, and 《CANCERS》. According to the results of reference and keyword analysis, "deep learning, nomogram, ultrasound, f-18-fdg, machine learning, covid-19, radiogenomics" has been determined as the main research direction in the future. Conclusion: Radiomics is in a phase of vigorous development with broad prospects. Cross-border cooperation between countries and institutions should be strengthened in the future. It can be predicted that the development of deep learning-based models and multimodal fusion models will be the focus of future research. Advances in knowledge: This study explores the current state of research and hot spots in the field of radiomics from multiple perspectives, comprehensively, and objectively reflecting the evolving trends in imaging-related research and providing a reference for future research.

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全球放射组学研究的趋势和热点:文献计量分析
目的:本研究的目的是总结基于放射组学的知识结构,并通过文献计量分析探讨潜在的趋势和优先事项。方法:从科学核心收藏网站上选择 2012 年至 2022 年 10 月与放射组学相关的出版物。使用 VOSviewer(1.6.18 版)、CiteSpace(6.1.3 版)、Tableau(2022 版)、Microsoft Excel 和 Rstudio 免费在线平台(http://bibliometric.com)对该领域中的国家、机构、作者、参考文献和关键词进行共同撰写、共同引用和共同出现分析。此外,还对其进行了可视化分析。研究结果研究共收录了 6428 篇文章。自 2012 年以来,基于放射组学的研究论文有所增加。从论文数量来看,中国在这一领域的贡献最大。我们发现,发表论文最多的机构和作者是复旦大学和天杰公司。发表论文最多的前三本杂志是《FRONTIERS IN ONCOLOGY》、《EUROPEAN RADIOLOGY》和《CANCERS》。根据参考文献和关键词分析结果,"深度学习、提名图、超声、f-18-fdg、机器学习、covid-19、放射基因组学 "被确定为未来的主要研究方向。结论放射组学正处于蓬勃发展阶段,前景广阔。未来应加强国家和机构间的跨界合作。可以预见,基于深度学习的模型和多模态融合模型的开发将是未来研究的重点。知识进步:本研究从多角度探讨了放射组学领域的研究现状和热点,全面、客观地反映了影像学相关研究的发展态势,为未来研究提供了参考。
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来源期刊
CiteScore
4.40
自引率
0.00%
发文量
202
审稿时长
2 months
期刊介绍: Technology in Cancer Research & Treatment (TCRT) is a JCR-ranked, broad-spectrum, open access, peer-reviewed publication whose aim is to provide researchers and clinicians with a platform to share and discuss developments in the prevention, diagnosis, treatment, and monitoring of cancer.
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